1. Field of the Invention
This invention relates generally to audience targeting and more particularly to an audience server for matching deliverable content such as advertising to an audience.
2. Description of the Related Art
Targeted marketing has long been known as an effective method for reaching consumers. When the consumer receives only relevant content (advertisements, etc.) from a provider, the consumer is more likely to patronize the particular provider, make purchases, and provide additional personal information that may assist in refining the provider's “view” of the consumer. As such, targeted marketing can lead to a more focused and robust interaction with the consumer. This, correspondingly, can lead to a more rewarding interaction for the provider by generating increased revenue.
In order to effectively target a consumer, it may be desirable for marketing systems to react to consumer information received from a variety of online and offline sources. These sources may include databases and servers, as well as multiple web properties within a network of affiliated websites. Moreover, the consumer information may be collected from a variety of sources in diverse formats. It may also be desirable for marketing systems to interact with the systems that actually deliver the content to the user. In short, an effective marketing system may appreciate the characteristics and preferences of a specific user regardless of the number or type of channels through which contact with the user is made.
Some known systems, however, are only adapted to receive information from a single source (e.g., registration information provided by the consumer). Other systems may receive information from multiple sources, but are unable to usefully combine information relating to the same consumer and communicate it to the necessary content delivery system. Thus, it may be desirable to have a system and method for delivering content that integrates with and aggregates data from various sources, including the underlying systems that deliver content to the consumer.
Known systems for delivering targeted content to consumers are focused on reaching the greatest quantity of consumers, without considering the value of interacting with each particular consumer. For example, some systems may deliver “targeted” content to each member of a group of consumers based on the fact that each subscribes to the same magazine. These systems, however, do not consider that only a portion of the group may make on-line purchases, for example, in addition to subscribing to the magazine. This failure to recognize and differentiate “valuable” consumers can lead to lost revenue for the content provider. In addition, the delivery of content to a significant volume of low-value consumers may expend valuable system resources. Accordingly, it may be desirable to have a means of delivering the appropriate content to the appropriate user in order to maximize the value of the relationship between the provider and the consumer.
Another problem with content delivery systems is that the information upon which targeting is based may rapidly become stale. An audience member deemed to have particular characteristics may no longer have such characteristics by the time content is delivered. New potential audience members may also become available after determination of a targeted group. The volatility of audience member characteristics and the high volume of information to be processed both present difficulties to systems that seek to target well tailored audiences. Content delivery systems are also often myopic, merely carrying out content delivery as dictated by the particular domain in which the system resides. This prevents appreciation of activities in other domains.
Still another problem with content delivery systems, particularly advertisement delivery systems, is that they are unduly contextual and reactive. The context of ad placement in a web page is not always indicative of the advertisement that is most appropriate for a requestor. For example, a requestor of a weather page is not necessarily interested in travel and golf advertisements, but may nevertheless be delivered such ads any time they request such a page. Additionally, reactive ad placement systems respond to a request for an advertisement, typically in reaction to information that is provided with the request. There may be information that is contained in connection with the current browsing activities of the user corresponding to the request. The solely reactive approach is by nature contextual, and is in other ways tied to the request itself. Accordingly, the decision as to which advertisement is most appropriate for the user ignores the individual characteristics of the user/requestor, and merely looks at information in the request.
It is also difficult for publishers to serve advertisements such that revenue is maximized, or accommodate proper serving of advertisements by third party providers. Finally, the allocation of credit and corresponding revenue for activities related to the serving of advertisements remains inadequate.